Expensive Report Audit

Aggregation Engine for an Online Insurance Aggregator


Industry

Accounting, Artificial Intelligence, Big Data, Enterprise Software, FinTech, Machine Learning, SaaS

Company Size

300+

Duration

1.5 years (on going)

Engineering for an Expense Report Auditing product

TechBulls partnered up with the client, with a product in automation of Expense Report Auditing, for doing their Product Engineering. We fixed and simplified parts of their product, and added various new features and integrated multiple third-party systems.

Client has an AI platform for modern finance teams. It automates a manual process, uncovers problems, and optimizes decision making for enterprises.

Over 1,000 global enterprises, including one-third of the Fortune 500, use Client’s Expense Audit and Autonomous AP products to replace manual finance processes and accelerate the speed and agility of their business.

What were the problem faced?

The client previously had engaged with another offshore development partner since the inception of the product. The code of the product had evolved to be clunky and grown difficult to maintain.

Certain parts of the system were not scalable and were an operational overhead. Debugging production issues was very difficult.

What were the challenges?

The client previously had engaged with another offshore development partner since the inception of the product. The code of the product had evolved to be clunky and grown difficult to maintain. Certain parts of the system were not scalable and were an operational overhead. Debugging production issues was very difficult.

The client tried to improve the process and overall product quality with help of internal people along with the external development partner which did not result in much success.

Engineering for an Expense Report Auditing product

UI code which was written in AngularJS with heavy usage of jQuery. Both did not go well together and resulted in code with thousands of lines of unreadable code.

The customer had a module for running scheduled jobs. This module had the ability to run schedules and run multiple jobs per customer. There were occasions when jobs did not fire or froze while running. Hung jobs caused database deadlock issues at times.

There was no way to track what a particular job was doing at a time.

The client was unable to roll out new features faster and a large part of the time was spent in managing production issues. The client was finding it difficult to onboard new customers due to delays in development. Inability to onboard a customer was a straight loss of business.

Proposed Solution

Our team rebuilt and restructured many modules. We cleaned up the UI code, removed jQuery and made it purely AngularJS which reduced the size of code by 50% and improved readability and maintainability significantly.

We redesigned the job scheduler module and added following features:

  • Created a basic framework around jobs.
  • The framework registers each job run within the database
  • The framework provides each job run with a unique id and includes the unique job id in the log files to improve traceability of jobs.
  • The framework created around jobs abstracted out the operations and reporting aspects, leaving the job developers to only focus on business logic.
  • Created alerts emails for events like a stuck job or a failed job.
  • We redesigned the job scheduler to be clustered. The jobs could run on multiple machines instead of single machines making it more scalable.
  • The redesign allowed the ops team to quickly identify issues and resolve the customer complaints in a timely manner. Ops overhead was reduced by 25%.

Additional
Service

Created an automated
functional testing rig

The client was on boarding the largest cloud company as a customer. The customer wanted that product to be periodically tested for security. The functional testing rig allowed us to do penetration testing as part of every build. The test rig was demonstrated to the customer and was a key for the client to acquire the customer.

Development
Process

We worked with the client to create a process through which it was easier to roll out weekly releases to production instead of monthly.

We set up a development process with a branching and merging strategy which was more suitable for frequent releases.

Third-Party
Integrations

We helped the client integrate with various third party expense management systems

to bring and audit the expenses from their system to the client's product. We extracted common components from integrations and created reusable API around them so that new integrations take lesser time to complete.

Improved trackability
for Ops team

We enriched the logs with essential parameters like logged in user, customer id, thread name etc. We helped customers setup tools like Kibana, Grafana and CloudWatch. This allowed the ops team to configure different triggers to generate alert emails. It was easier debugging things due to the introduction of Kibana.

Development of
Manager Dashboard

We helped the customer build the “Manager Dashboard” feature. The dashboard was a near real-time snapshot of data. It also had the ability to filter and project by different metrics. The dashboard data was generated by performing complex calculations within Spark.

How did the client benefit?

  • The UI code was significantly reduced and became more readable and maintainable.
  • The job scheduler was made a lot more scalable.
  • Debugging and troubleshooting became extremely easy for the Ops team and they could react to customer issues much faster.
  • Frequent release cycles allowed clients to roll out fixes and new features more frequently.
  • The client could onboard a lot more customers due to integrations with third-party systems.

Used
Technologies

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